BigDat 2020: regular registration January 10*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
********************************************************
6th INTERNATIONAL WINTER SCHOOL ON BIG DATA
BigDat 2020
Ancona, Italy
January 13-17, 2020
Co-organized by:
Department of Information Engineering, Marche Polytechnic University
Institute for Research Development, Training and Advice (IRDTA)
Brussels / London
https://bigdat2020.irdta.eu/
********************************************************
--- Regular registration deadline: January 10, 2020 ---
********************************************************
SCOPE:
BigDat 2020 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data, which covers a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, medicine, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, security and privacy, and applications (to biological and health sciences, to business, finance and transportation, to online social networks, etc.). Major challenges of analytics, management and storage of big data will be identified through 21 four-hour and a half courses and 1 round table, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
ADDRESSED TO:
Master's students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2020 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators.
STRUCTURE:
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
VENUE:
BigDat 2020 will take place in Ancona, a city founded by Greek settlers and today one of the main ports on the Adriatic Sea. The venue will be:
Department of Information Engineering
Marche Polytechnic University
Via Brecce Bianche 12
60131 Ancona
PROFESSORS AND COURSES:
Sanchita Bhattacharya (University of California, San Francisco), [introductory/advanced] Big Data in Immunology: Sharing, Dissemination, and Repurposing
Diego Calvanese (Free University of Bozen-Bolzano), [introductory] Virtual Knowledge Graphs for Data Integration
Sheelagh Carpendale (University of Calgary), [introductory] Data Visualization
Nitesh V. Chawla (University of Notre Dame), [intermediate/advanced] Learning in the Presence of Class Imbalance and Changing Distributions
Amr El Abbadi (University of California, Santa Barbara), [introductory/intermediate] An Introduction to Blockchain
Charles Elkan (University of California, San Diego), [intermediate] A Rapid Introduction to Modern Deep Learning
Minos Garofalakis (Technical University of Crete), [intermediate/advanced] Private Data Analytics at Scale
Jiawei Han (University of Illinois, Urbana-Champaign), [intermediate/advanced] From Unstructured Text to TextCube: Automated Construction and Multidimensional Exploration
Craig Knoblock (University of Southern California), [intermediate/advanced] Building Knowledge Graphs
Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences
Bamshad Mobasher (DePaul University), [intermediate] Context-aware Recommender Systems
Jayanti Prasad (Embold Technologies), [introductory/intermediate] Big Code
Lior Rokach and Bracha Shapira (Ben-Gurion University of the Negev), [introductory/intermediate] Recommender Systems
Peter Rousseeuw (KU Leuven), [introductory] Anomaly Detection by Robust Methods
Asim Roy (Arizona State University), [intermediate] Hardware-based (GPU, FPGA based) Machine Learning That Exploits Massively Parallel Computing – An Overview of Concepts, Architectures and Neural Network Algorithm Implementation
Hanan Samet (University of Maryland), [introductory/intermediate] Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), and Location-based Services
Rory Smith (Monash University), [introductory/intermediate] Learning from Data, the Bayesian Way
Jaideep Srivastava (University of Minnesota), [introductory/intermediate] Social Computing
Mayte Suárez-Fariñas (Icahn School of Medicine at Mount Sinai), [intermediate/advanced] Meta-analysis Methods for High-dimensional Data
Jeffrey Ullman (Stanford University), [introductory] Big-data Algorithms That Aren't Machine Learning (remote)
Wil van der Aalst (RWTH Aachen University), [introductory/intermediate] Process Mining: A Very Different Kind of Machine Learning That Can Be Applied in Any Organization
OPEN SESSION
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing title, authors, and summary of the research to david(a)irdta.eu by January 5, 2020.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by January 5, 2020.
EMPLOYER SESSION:
Firms searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for, to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by January 5, 2020.
ORGANIZING COMMITTEE:
Emanuele Frontoni (Ancona, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
Flavio Tonetto (Ancona, industrial chair)
Domenico Ursino (Ancona, co-chair)
REGISTRATION:
It has to be done at
https://bigdat2020.irdta.eu/registration/
The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration facility disabled when the capacity of the venue is exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
ACCOMMODATION:
Suggestions for accommodation are available at
https://bigdat2020.irdta.eu/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david(a)irdta.eu
ACKNOWLEDGMENTS:
Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche
Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
CONFINDUSTRIA Marche Nord
CINI AIIS National Lab
CINI Big Data Laboratory
DeepLearn 2020: early registration December 27*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
***************************************************************
4th INTERNATIONAL SUMMER SCHOOL ON DEEP LEARNING
DeepLearn 2020
León, Guanajuato, Mexico
July 27-31, 2020
Co-organized by:
Center for Research in Mathematics, A.C. (CIMAT-CONACyT)
Guanajuato
Institute for Research Development, Training and Advice (IRDTA)
Brussels/London
https://deeplearn2020.irdta.eu/
***************************************************************
--- Early registration deadline: December 27, 2019 ---
***************************************************************
SCOPE:
DeepLearn 2020 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova and Warsaw.
Deep learning is a branch of artificial intelligence covering a spectrum of current exciting research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most deep learning subareas will be displayed, and main challenges identified through 2 keynote lectures and 24 four-hour and a half courses, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
ADDRESSED TO:
Master's students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2020 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators.
STRUCTURE:
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
VENUE:
DeepLearn 2020 will take place in León, the most populous city in the state of Guanajuato, in central Mexico, and a major economic pole in the country with specialization in leather industry. The venue will be:
Poliforum León
Blvd. Adolfo López Mateos esq. Blvd. Francisco Villa
Col. Oriental, León, Gto., Mexico, C.P. 37510
KEYNOTE SPEAKERS: (to be completed)
Maja Pantic (Imperial College London), Artificial Emotional Intelligence, Faces, Deep Fakes and Other Topics
PROFESSORS AND COURSES: (to be completed)
Georgios Giannakis (University of Minnesota), [advanced] Ensembles for Interactive and Deep Learning Machines with Scalability, Expressivity, and Adaptivity
Jose Principe (University of Florida), [intermediate/advanced] Cognitive Architectures for Object Recognition in Video
Fedor Ratnikov (National Research University Higher School of Economics), [introductory] Specifics of Applying Machine Learning to Problems in Natural Science
Björn Schuller (Imperial College London), [introductory/intermediate] Deep Signal Processing
Alex Smola (Amazon), [introductory/advanced] Dive into Deep Learning
Kunal Talwar (Google Brain), [intermediate] Differentially Private Machine Learning
René Vidal (Johns Hopkins University), [intermediate/advanced] Mathematics of Deep Learning
Ming-Hsuan Yang (University of California, Merced), [intermediate/advanced] Learning to Track Objects
OPEN SESSION:
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david(a)irdta.eu by July 19, 2020.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by July 19, 2020.
EMPLOYER SESSION:
Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for, to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by July 19, 2020.
ORGANIZING COMMITTEE:
Teresa Efigenia Alarcón Martínez (Guadalajara)
Oscar Dalmau Cedeño (Guanajuato, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
REGISTRATION:
It has to be done at
https://deeplearn2020.irdta.eu/registration/
The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue is exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
ACCOMMODATION:
Suggestions for accommodation will be available in due time
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david(a)irdta.eu
ACKNOWLEDGMENTS:
Centro de Investigación en Matemáticas, A.C. (CIMAT-CONACyT) – Guanajuato
Centro Universitario de los Valles, Universidad de Guadalajara
Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
AlCoB 2020: call for posters*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
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The 7th International Conference on Algorithms for Computational Biology (AlCoB 2020) invites researchers to submit poster presentations. AlCoB 2020 will be held in Missoula, Montana on April 13-15, 2020. See:
https://alcob2020.irdta.eu/
Poster presentations are intended to enhance informal interactions with conference participants, at the same time allowing for in-depth discussion.
TOPICS
Presentations displaying novel work in progress on algorithms in computational biology are encouraged on the following topics:
- assembling sequence reads into a complete genome,
- identifying gene structures in the genome,
- recognizing regulatory motifs,
- aligning nucleotides and comparing genomes,
- reconstructing regulatory networks of genes, and
- inferring the evolutionary phylogeny of species.
Posters do not need to show final research results. Work that might lead to new interesting developments is welcome.
KEY DATES
Poster submission deadline: March 6, 2020
Notification of poster acceptance or rejection: March 13, 2020
SUBMISSION
Please upload a .pdf submission to:
https://easychair.org/conferences/?conf=alcob2020
It should contain the title, author(s) and affiliation, and should not exceed 500 words.
PRESENTATION
Posters will be allocated 10 minutes each in the programme for oral presentation. Moreover, they will remain hanging out during the whole conference for discussion.
PUBLICATION
Posters will not appear in the LNCS/LNBI proceedings volume of AlCoB 2020. However, they will be eligible for submission to the post-conference journal special issue.
REGISTRATION
At least one author of each accepted poster must register to the conference by March 20, 2020. The registration fare is reduced: 285 Euros. It gives the same rights all other conference participants will have (attendance, copy of the proceedings volume, coffee breaks, lunches). Contributors of regular papers who in addition get a poster accepted must register for the latter independently.
DeepLearn 2020: early registration December 27*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
***************************************************************
4th INTERNATIONAL SUMMER SCHOOL ON DEEP LEARNING
DeepLearn 2020
León, Guanajuato, Mexico
July 27-31, 2020
Co-organized by:
Center for Research in Mathematics, A.C. (CIMAT-CONACyT)
Guanajuato
Institute for Research Development, Training and Advice (IRDTA)
Brussels/London
https://deeplearn2020.irdta.eu/
***************************************************************
--- Early registration deadline: December 27, 2019 ---
***************************************************************
SCOPE:
DeepLearn 2020 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova and Warsaw.
Deep learning is a branch of artificial intelligence covering a spectrum of current exciting research and industrial innovation that provides more efficient algorithms to deal with large-scale data in neurosciences, computer vision, speech recognition, language processing, human-computer interaction, drug discovery, biomedical informatics, healthcare, recommender systems, learning theory, robotics, games, etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most deep learning subareas will be displayed, and main challenges identified through 2 keynote lectures and 24 four-hour and a half courses, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
ADDRESSED TO:
Master's students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2020 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators.
STRUCTURE:
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
VENUE:
DeepLearn 2020 will take place in León, the most populous city in the state of Guanajuato, in central Mexico, and a major economic pole in the country with specialization in leather industry. The venue will be:
Poliforum León
Blvd. Adolfo López Mateos esq. Blvd. Francisco Villa
Col. Oriental, León, Gto., Mexico, C.P. 37510
KEYNOTE SPEAKERS: (to be completed)
Maja Pantic (Imperial College London), Artificial Emotional Intelligence, Faces, Deep Fakes and Other Topics
PROFESSORS AND COURSES: (to be completed)
Georgios Giannakis (University of Minnesota), [advanced] Ensembles for Interactive and Deep Learning Machines with Scalability, Expressivity, and Adaptivity
Jose Principe (University of Florida), [intermediate/advanced] Cognitive Architectures for Object Recognition in Video
Fedor Ratnikov (National Research University Higher School of Economics), [introductory] Specifics of Applying Machine Learning to Problems in Natural Science
Björn Schuller (Imperial College London), [introductory/intermediate] Deep Signal Processing
Alex Smola (Amazon), [introductory/advanced] Dive into Deep Learning
Kunal Talwar (Google Brain), tba
René Vidal (Johns Hopkins University), [intermediate/advanced] Mathematics of Deep Learning
Ming-Hsuan Yang (University of California, Merced), [intermediate/advanced] Learning to Track Objects
OPEN SESSION:
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david(a)irdta.eu by July 19, 2020.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by July 19, 2020.
EMPLOYER SESSION:
Firms searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for, to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by July 19, 2020.
ORGANIZING COMMITTEE:
Teresa Efigenia Alarcón Martínez (Guadalajara)
Oscar Dalmau Cedeño (Guanajuato, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
REGISTRATION:
It has to be done at
https://deeplearn2020.irdta.eu/registration/
The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue is exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
ACCOMMODATION:
Suggestions for accommodation will be available in due time
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david(a)irdta.eu
ACKNOWLEDGMENTS:
Centro de Investigación en Matemáticas, A.C. (CIMAT-CONACyT) – Guanajuato
Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
BigDat 2020: early registration December 16*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
********************************************************
6th INTERNATIONAL WINTER SCHOOL ON BIG DATA
BigDat 2020
Ancona, Italy
January 13-17, 2020
Co-organized by:
Department of Information Engineering, Marche Polytechnic University
Institute for Research Development, Training and Advice (IRDTA)
Brussels / London
https://bigdat2020.irdta.eu/
********************************************************
--- Early registration deadline: December 16, 2019 ---
********************************************************
SCOPE:
BigDat 2020 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data, which covers a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, medicine, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, security and privacy, and applications (to biological and health sciences, to business, finance and transportation, to online social networks, etc.). Major challenges of analytics, management and storage of big data will be identified through 22 four-hour and a half courses and 1 round table, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
ADDRESSED TO:
Master's students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2020 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators.
STRUCTURE:
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
VENUE:
BigDat 2020 will take place in Ancona, a city founded by Greek settlers and today one of the main ports on the Adriatic Sea. The venue will be:
Department of Information Engineering
Marche Polytechnic University
Via Brecce Bianche 12
60131 Ancona
PROFESSORS AND COURSES:
Sanchita Bhattacharya (University of California, San Francisco), [introductory/advanced] Big Data in Immunology: Sharing, Dissemination, and Repurposing
Diego Calvanese (Free University of Bozen-Bolzano), [introductory] Virtual Knowledge Graphs for Data Integration
Sheelagh Carpendale (University of Calgary), [introductory] Data Visualization
Nitesh V. Chawla (University of Notre Dame), [intermediate/advanced] Learning in the Presence of Class Imbalance and Changing Distributions
Amr El Abbadi (University of California, Santa Barbara), [introductory/intermediate] An Introduction to Blockchain
Charles Elkan (University of California, San Diego), [intermediate] A Rapid Introduction to Modern Deep Learning
Minos Garofalakis (Technical University of Crete), [intermediate/advanced] Private Data Analytics at Scale
Jiawei Han (University of Illinois, Urbana-Champaign), [intermediate/advanced] From Unstructured Text to TextCube: Automated Construction and Multidimensional Exploration
Xiaohua Tony Hu (Drexel University), [introductory/advanced] Machine Learning Methods for Big Microbiome Data Analysis
Craig Knoblock (University of Southern California), [intermediate/advanced] Building Knowledge Graphs
Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences
Bamshad Mobasher (DePaul University), [intermediate] Context-aware Recommender Systems
Jayanti Prasad (Embold Technologies), [introductory/intermediate] Big Code
Lior Rokach and Bracha Shapira (Ben-Gurion University of the Negev), [introductory/intermediate] Recommender Systems
Peter Rousseeuw (KU Leuven), [introductory] Anomaly Detection by Robust Methods
Asim Roy (Arizona State University), [intermediate] Hardware-based (GPU, FPGA based) Machine Learning That Exploits Massively Parallel Computing – An Overview of Concepts, Architectures and Neural Network Algorithm Implementation
Hanan Samet (University of Maryland), [introductory/intermediate] Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), and Location-based Services
Rory Smith (Monash University), [introductory/intermediate] Learning from Data, the Bayesian Way
Jaideep Srivastava (University of Minnesota), [introductory/intermediate] Social Computing
Mayte Suárez-Fariñas (Icahn School of Medicine at Mount Sinai), [intermediate/advanced] Meta-analysis Methods for High-dimensional Data
Jeffrey Ullman (Stanford University), [introductory] Big-data Algorithms That Aren't Machine Learning (remote)
Wil van der Aalst (RWTH Aachen University), [introductory/intermediate] Process Mining: A Very Different Kind of Machine Learning That Can Be Applied in Any Organization
OPEN SESSION
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing title, authors, and summary of the research to david(a)irdta.eu by January 5, 2020.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by January 5, 2020.
EMPLOYER SESSION:
Firms searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for, to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by January 5, 2020.
ORGANIZING COMMITTEE:
Emanuele Frontoni (Ancona, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
Flavio Tonetto (Ancona, industrial chair)
Domenico Ursino (Ancona, co-chair)
REGISTRATION:
It has to be done at
https://bigdat2020.irdta.eu/registration/
The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration facility disabled when the capacity of the venue is exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
ACCOMMODATION:
Suggestions for accommodation are available at
https://bigdat2020.irdta.eu/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david(a)irdta.eu
ACKNOWLEDGMENTS:
Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche
Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
CONFINDUSTRIA Marche Nord
CINI AIIS National Lab
CINI Big Data Laboratory
AlCoB 2020: extended submission deadline December 9*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
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***** SUBMISSION DEADLINE EXTENDED: December 9 *****
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7th INTERNATIONAL CONFERENCE ON ALGORITHMS FOR COMPUTATIONAL BIOLOGY
AlCoB 2020
Missoula, Montana, USA
April 13-15, 2020
Co-organized by:
Department of Computer Science
University of Montana
and
Institute for Research Development, Training and Advice
Brussels/London
https://alcob2020.irdta.eu
**********************************************************************************
AIMS:
AlCoB aims at promoting and displaying excellent research using string and graph algorithms and combinatorial optimization to deal with problems in biological sequence analysis, genome rearrangement, phylogeny reconstruction, and structure prediction.
Previous events were held in Tarragona, Mexico City, Trujillo (Spain), Aveiro, Hong Kong and Berkeley.
The conference will address several of the current challenges in computational biology, with topics including:
1) assembling sequence reads into a complete genome,
2) identifying gene structures in the genome,
3) recognizing regulatory motifs,
4) aligning nucleotides and comparing genomes,
5) reconstructing regulatory networks of genes, and
6) inferring the evolutionary phylogeny of species.
Special focus will be put on methodology and significant room will be reserved for scholars at the beginning of their career.
VENUE:
AlCoB 2020 will take place in Missoula, Montana, a college town located in the heart of the Rocky Mountains, near Glacier National Park and Yellowstone National Park. The meeting will be hosted in the University Center, a few hundred feet from the base of Mount Sentinel.
SCOPE:
Topics of either theoretical or applied interest include, but are not limited to:
Sequence analysis
Sequence alignment
Sequence assembly
Genome rearrangement
Regulatory motif finding
Phylogeny reconstruction
Phylogeny comparison
Structure prediction
Compressive genomics
Proteomics: molecular pathways, interaction networks, mass spectrometry analysis
Transcriptomics: splicing variants, isoform inference and quantification, differential analysis
Next-generation sequencing: population genomics, metagenomics, metatranscriptomics, epigenomics
Genome CD architecture
Microbiome analysis
Cancer computational biology
Systems biology
STRUCTURE:
AlCoB 2020 will consist of:
invited lectures
peer-reviewed contributions
posters
KEYNOTE SPEAKERS:
Terry Gaasterland (University of California, San Diego), Genetic Risk of Disease through Genome Variation and Regulation of Transcription
Christine Orengo (University College London), Algorithms for Mining Massive Metagenome Repositories to Detect Novel Enzymes
Tamar Schlick (New York University), Folding Genes at Nucleosome Resolution
PROGRAMME COMMITTEE:
Mani Arumugam (University of Copenhagen, DK)
Colin Dewey (University of Wisconsin, Madison, US)
Joe Felsenstein (University of Washington, US)
Olivier Gascuel (Pasteur Institute, FR)
Debashis Ghosh (University of Colorado, US)
Daniel Huson (University of Tübingen, DE)
Miriam Konkel (Clemson University, US)
Alla Lapidus (Saint Petersburg State University, RU)
Aron Marchler-Bauer (National Center for Biotechnology Information, US)
Maria-Jesus Martin (European Bioinformatics Institute, UK)
Carlos Martín-Vide (Rovira i Virgili University, ES, chair)
David H. Mathews (University of Rochester, US)
Aaron McKenna (Dartmouth College, US)
Ryan E. Mills (University of Michigan, US)
Burkhard Morgenstern (University of Göttingen, DE)
Sayan Mukherjee (Duke University, US)
Houtan Noushmehr (Henry Ford Health System, US)
Knut Reinert (Free University of Berlin, DE)
Joel Rozowsky (Yale University, US)
Russell Schwartz (Carnegie Mellon University, US)
Temple F. Smith (Boston University, US)
James Taylor (Johns Hopkins University, US)
Zlatko Trajanoski (Medical University of Innsbruck, AT)
David A. Wheeler (Baylor College of Medicine, US)
Travis Wheeler (University of Montana, US)
Shibu Yooseph (University of Central Florida, US)
ORGANIZING COMMITTEE:
Sara Morales (Brussels)
Manuel Parra-Royón (Granada)
David Silva (London, co-chair)
Miguel A. Vega-Rodríguez (Cáceres)
Travis Wheeler (Missoula, co-chair)
SUBMISSIONS:
Authors are invited to submit non-anonymized papers in English presenting original and unpublished research. Papers should not exceed 12 single-spaced pages (all included) and should be prepared according to the standard format for Springer Verlag's LNCS series (see http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0).
Upload submissions to:
https://easychair.org/conferences/?conf=alcob2020
PUBLICATIONS:
A volume of proceedings published by Springer in the LNCS/LNBI series will be available by the time of the conference.
A special issue of a major journal will be later published containing peer-reviewed substantially extended versions of some of the papers contributed to the conference. Submissions to it will be by invitation.
REGISTRATION:
The registration form can be found at:
https://alcob2020.irdta.eu/registration/
DEADLINES (all at 23:59 CET):
Paper submission: December 9, 2019 – EXTENDED
Notification of paper acceptance or rejection: January 6, 2020
Final version of the paper for the LNCS/LNBI proceedings: January 13, 2020
Early registration: January 13, 2020
Late registration: March 30, 2020
Submission to the journal special issue: July 15, 2020
QUESTIONS AND FURTHER INFORMATION:
david (at) irdta.eu
ACKNOWLEDGEMENTS:
University of Montana
IRDTA – Institute for Research Development, Training and Advice, Brussels/London
Liebe D-CONler / Dear Concurrency Theorists!
As already announced, the next edition of D-CON will be hosted in
*Duisburg* at the University of Duisburg-Essen on *March 12th - March
13th 2020*.
The related web page for D-CON 2020 can be found here:
https://udue.de/dcon2020
We are very happy to announce two invited talks by:
- Ana Sokolova (University of Salzburg)
- Paolo Baldan (University of Padova)
You can now register for participation by sending an email to
ti(a)uni-due.de <mailto:ti@uni-due.de>. The participation fee will be a
moderate fee of less than 100€. Due to environmental reasons, we would
like to ask you to travel by train if possible and plan to (slightly)
reduce the fee for following this request.
Please use the following template for registration:
----
- Name (for name tags):
- Affiliation (for name tags):
- Date of Arrival:
- Date of Departure:
- I will join (self-paid) dinner on Wednesday (yes/no) (central location
in Duisburg, yet to be determined):
- I will join (self-paid) dinner on Thursday (yes/no) (location at
Duisburg Innenhafen, yet to be determined):
- Dietary restrictions (if any):
- Planned transportation:
-----
If you would like to give a talk, please send a *title* and short
*abstract* and keep in mind the newly established different *talk
lengths*. Please specify the kind of talk and choose one of the
following talk-lengths that suits the scope of your presented work best:
15, 30, 45 minutes.
- Regular talk
- Tutorial talk
- Lightning talk
The deadline for contribution proposals and for registrations is on the
*25th of January 2020*.
We are looking forward to seeing you at D-CON 2020!
Best regards,
Rebecca, Richard and the rest of the group.
BigDat 2020: early registration December 16*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
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6th INTERNATIONAL WINTER SCHOOL ON BIG DATA
BigDat 2020
Ancona, Italy
January 13-17, 2020
Co-organized by:
Department of Information Engineering, Marche Polytechnic University
Institute for Research Development, Training and Advice (IRDTA)
Brussels / London
https://bigdat2020.irdta.eu/
********************************************************
--- Early registration deadline: December 16, 2019 ---
********************************************************
SCOPE:
BigDat 2020 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data, which covers a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, medicine, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, security and privacy, and applications (to biological and health sciences, to business, finance and transportation, to online social networks, etc.). Major challenges of analytics, management and storage of big data will be identified through 22 four-hour and a half courses and 1 round table, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
ADDRESSED TO:
Master's students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2020 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators.
STRUCTURE:
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
VENUE:
BigDat 2020 will take place in Ancona, a city founded by Greek settlers and today one of the main ports on the Adriatic Sea. The venue will be:
Department of Information Engineering
Marche Polytechnic University
Via Brecce Bianche 12
60131 Ancona
PROFESSORS AND COURSES:
Sanchita Bhattacharya (University of California, San Francisco), [introductory/advanced] Big Data in Immunology: Sharing, Dissemination, and Repurposing
Diego Calvanese (Free University of Bozen-Bolzano), [introductory] Virtual Knowledge Graphs for Data Integration
Sheelagh Carpendale (University of Calgary), [introductory] Data Visualization
Nitesh V. Chawla (University of Notre Dame), [intermediate/advanced] Learning in the Presence of Class Imbalance and Changing Distributions
Amr El Abbadi (University of California, Santa Barbara), [introductory/intermediate] An Introduction to Blockchain
Charles Elkan (University of California, San Diego), [intermediate] A Rapid Introduction to Modern Deep Learning
Minos Garofalakis (Technical University of Crete), [intermediate/advanced] Private Data Analytics at Scale
Jiawei Han (University of Illinois, Urbana-Champaign), [intermediate/advanced] From Unstructured Text to TextCube: Automated Construction and Multidimensional Exploration
Xiaohua Tony Hu (Drexel University), [introductory/advanced] Machine Learning Methods for Big Microbiome Data Analysis
Craig Knoblock (University of Southern California), [intermediate/advanced] Building Knowledge Graphs
Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences
Bamshad Mobasher (DePaul University), [intermediate] Context-aware Recommender Systems
Jayanti Prasad (Embold Technologies), [introductory/intermediate] Big Code
Lior Rokach and Bracha Shapira (Ben-Gurion University of the Negev), [introductory/intermediate] Recommender Systems
Peter Rousseeuw (KU Leuven), [introductory] Anomaly Detection by Robust Methods
Asim Roy (Arizona State University), [intermediate] Hardware-based (GPU, FPGA based) Machine Learning That Exploits Massively Parallel Computing – An Overview of Concepts, Architectures and Neural Network Algorithm Implementation
Hanan Samet (University of Maryland), [introductory/intermediate] Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial and Spatio-textual Databases, Geographic Information Systems (GIS), and Location-based Services
Rory Smith (Monash University), [introductory/intermediate] Learning from Data, the Bayesian Way
Jaideep Srivastava (University of Minnesota), [introductory/intermediate] Social Computing
Mayte Suárez-Fariñas (Icahn School of Medicine at Mount Sinai), [intermediate/advanced] Meta-analysis Methods for High-dimensional Data
Jeffrey Ullman (Stanford University), [introductory] Big-data Algorithms That Aren't Machine Learning (remote)
Wil van der Aalst (RWTH Aachen University), [introductory/intermediate] Process Mining: A Very Different Kind of Machine Learning That Can Be Applied in Any Organization
OPEN SESSION
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing title, authors, and summary of the research to david(a)irdta.eu by January 5, 2020.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by January 5, 2020.
EMPLOYER SESSION:
Firms searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for, to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david(a)irdta.eu by January 5, 2020.
ORGANIZING COMMITTEE:
Emanuele Frontoni (Ancona, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
Flavio Tonetto (Ancona, industrial chair)
Domenico Ursino (Ancona, co-chair)
REGISTRATION:
It has to be done at
https://bigdat2020.irdta.eu/registration/
The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration facility disabled when the capacity of the venue is exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
ACCOMMODATION:
Suggestions for accommodation are available at
https://bigdat2020.irdta.eu/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david(a)irdta.eu
ACKNOWLEDGMENTS:
Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche
Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
CONFINDUSTRIA Marche Nord
CINI AIIS National Lab
CINI Big Data Laboratory